NMR, crystallographic and computational investigations of peptides, proteins and bisphosphonates: New paradigms for rational drug design
The standard approaches to lead identification and optimization involve a long and expensive process including random and nonrandom (targeted or focused) screening. Given the limited success of these standard approaches, an alternate route to develop a new drug would be to start with an existing one. There are many advantages to this strategy since in many cases the "leads" will be in current use in humans or will have been in clinical trials which greatly enhances the likelihood of them being safe for other indications, increasing the probability of eventually obtaining a real drug (as opposed to just an inhibitor). This dissertation explores the potential use of bisphosphonates, a class of molecules currently used clinically in humans for treating bone resorption diseases like osteoporosis, Paget's disease etc, as anti-parasitic, anti-bacterial and anti-cancer agents. The focus of this work can be broadly divided into three areas: (1) using NMR, x-ray crystallography and quantum chemistry to understand protein-ligand interactions, (2) employing computational modeling to gain insights into catalytic mechanisms and evolutionary origins of terpene synthases and cyclases, and finally (3) developing mathematical models based on enzyme-inhibition data and molecular descriptors to predict potency/activity of compounds in cell-based assays.